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Rafał Szlendak

2 accepted papers

2024

Understanding Progressive Training Through the Framework of Randomized Coordinate Descent

AISTATS 2024poster

We propose a Randomized Progressive Training algorithm (RPT)—a stochastic proxy for the well-known Progressive Training method (PT) (Karras et al., 2017). Originally designed to train GANs (Goodfellow et al., 2014), PT was proposed as a heuristic, with no convergence analysis even for the simplest o…

Cited by 4SourcePDFScholar
2022

Permutation Compressors for Provably Faster Distributed Nonconvex Optimization

ICLR 2022poster

In this work we study the MARINA method of Gorbunov et al (ICML, 2021) -- the current state-of-the-art distributed non-convex optimization method in terms of theoretical communication complexity. Theoretical superiority of this method can be largely attributed to two sources: a carefully engineered…

Cited by 44SourcePDFScholar